Machine Learning & Analytics Software Engineer, OS Power & Performance

Machine Learning & Analytics Software Engineer, OS Power & Performance

Great performance is critical to Apple's product experience. Would you like to help with quantitative analysis of high dimensional data to draw insights that would impact hundreds of millions of users? Does the idea of developing software to analyze system power and performance excite you? If this describes you, we would love to hear from you!

Description

We're looking for a proactive & impact-driven software engineer with excellent analytics, machine learning, problem solving and communication skills. You will need to analyze high dimensional data to derive meaningful insights. You will be responsible for developing models, metrics, tools, dashboards, reports, and infrastructure for streamlined analysis & communication of insights from large datasets. To be successful in this role, you must have a strong foundation in statistical analysis and the ability to apply it to solving business & product-development problems. You must also have a strong software engineering background and be able to write production level code. As a member of this team, you will have the opportunity to provide meaningful insights to teams and influence decisions across Apple on a broad range of products!

Minimum Qualifications

• Strong Quantitative Foundation and Technical Skills: Bachelor's degree in Computer Science, Electrical Engineering, or a related quantitative field (strong mathematical foundations, software engineering, broad knowledge of data analysis and practical machine learning)
• Data Engineering and Analytics: Skilled at scalably transforming raw data into actionable insights through practical problem formulation followed by building of ETL processes (e.g. Python & Spark) and data visualizations (e.g. Tableau)
• Business Acumen and Problem-Solving: Ability to understand the broader business context, solve complex problems, and communicate findings effectively to stakeholders.
• Adaptability and Collaboration: Comfortable with ambiguity, eager to learn, and capable of working effectively in a collaborative environment. Strong interpersonal skills and the ability to build relationships with diverse stakeholders are essential.

Preferred Qualifications

• M.S. or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, Statistics, or a similar quantitative field, with strong statistical skills and intuition
• Proficiency in distributed compute & storage technologies such as HDFS, S3, Iceberg, Spark, and Trino
• Proficiency with designing ETL flows and automation/scheduling (e.g. Kubernetes and Airflow)
• Working knowledge of Operating Systems (memory management, thread/process lifecycles, file systems, etc.)
• Experience driving cross-functional projects with diverse sets of stakeholders
• Skilled at connecting data insights to the company's overall strategy and objectives.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.